Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/16583#discussion_r96122416
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/HiveDDLSuite.scala
---
@@ -247,6 +247,16 @@ class HiveDDLSuite
}
}
+ test("SPARK-19129: drop partition with a empty string will drop the
whole table") {
+ val df = spark.createDataFrame(Seq((0, "a"), (1,
"b"))).toDF("partCol1", "name")
+
df.write.mode("overwrite").partitionBy("partCol1").saveAsTable("partitionedTable")
+ val e = intercept[AnalysisException] {
+ spark.sql("alter table partitionedTable drop partition(partCol1='')")
--- End diff --
@tejasapatil Thank you for your research
So far, we are not completely following Hive in the partition-related DDL
commands. `DROP PARTITION` is an example. If the users-specified spec does not
exist, we will throw an exception. Instead, Hive just silently ignores it
without any exception, but Hive will always report which partition is dropped
after the command. Thus, maybe we can improve this in the future PR.
Thus, this PR is to follow the same way to block the invalid inputs. That
is, throwing an exception when the input partition spec is not valid.
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